Management of massively distributed internet of things (IOT) gateways based on software-defined networking (SDN) via fly-by master drones

ABSTRACT

Massively distributed and low-cost Internet of things (IoT) gateways can be controlled by software-defined networking (SDN) protocols transferred via an autonomous mobile device (e.g., fly-by drone). The IoT gateways can comprise sensors that capture information that is transferred to the communication network via the autonomous mobile device. For example, the autonomous mobile device can wake the IoT gateways adaptively and perform data collection and/or configuration tasks. Further, the autonomous mobile device can deliver the collected data to network devices of the communication network and return for the next batch of IoT gateway data collections.

TECHNICAL FIELD

The subject disclosure relates to wireless communications, e.g.,management of massively distributed Internet of things (IoT) gatewaysbased on software-defined networking (SDN) via fly-by master drones.

BACKGROUND

Internet of things (IoT) technology holds a great promise for the futureof the global communications industry. As the number of connecteddevices that can establish connectivity with other devices and/orpassive objects to exchange data continues to rise steadily, the IoTtechnology gains widespread proliferation in the information technologyindustry. With an anticipated projection of over 20 billion devices inthe next few years, service providers, network providers and/or cloudproviders will observe a net increase in their traffic handlingcapabilities. This can help the providers enable new IoT servicestailored to targeted industry verticals. While there are several ongoingcompetitive developments in the IoT domain, some key areas where thereis an immediate focus include smart agriculture, smart city,transportation and/or utility services, virtual and augmented reality,etc. Low power wide area networking technologies using third generationpartnership project (3GPP) defined standards and their ongoing evolutiontowards fifth generation (5G) seem to provide a solid framework tosupport such massive IoT initiatives.

Typically, remote areas with limited network coverage or without networkcoverage cannot leverage these services. Offering IoT services in suchregions can create new challenges for network providers.

The above-described background relating to mobility networks is merelyintended to provide a contextual overview of some current issues and isnot intended to be exhaustive. Other contextual information may becomefurther apparent upon review of the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example system that depicts a high-level networkarchitecture that facilitates data analytics for Internet of things(IoT) fields.

FIGS. 2A-2B illustrate example systems that facilitate management of IoTgateways via a fly-by drone.

FIG. 3 illustrates an example system that comprises an IoT gateway thatis managed by a software-defined networking (SDN) cloud by utilizingfly-by drone(s).

FIG. 4 illustrates an example system comprising a fly-by drone that canbe utilized to facilitate communication between distributed IoT gatewaysand a SDN cloud of a mobility network.

FIG. 5 illustrates an example system that provides IoT services todistributed IoT gateways via one or more fly-by drones.

FIG. 6 illustrates an example system that facilitates automating one ormore features in accordance with the subject embodiments.

FIG. 7 illustrates an example method that facilitates utilization ofSDN-controlled massively distributed IoT gateways to enable IoTservices.

FIG. 8 illustrates an example method for utilizing a fly-by drone tofacilitate communication between a SDN cloud and distributed IoTgateways.

FIG. 9 illustrates an example method for managing distributed IoTgateways based on instructions received from a SDN cloud that aredelivered via an autonomous mobile device.

FIG. 10 illustrates an example method for managing an autonomous mobiledevice utilized to facilitate communications between distributed IoTgateways and a communication network.

FIG. 11 illustrates an example method for monitoring information sensedby distributed IoT gateways that communicate with a SDN cloud via anautonomous mobile device.

FIG. 12 illustrates a block diagram of a computer operable to executethe disclosed communication architecture.

FIG. 13 illustrates a schematic block diagram of a computing environmentin accordance with the subject specification.

DETAILED DESCRIPTION

One or more embodiments are now described with reference to thedrawings, wherein like reference numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of the various embodiments. It may be evident,however, that the various embodiments can be practiced without thesespecific details, e.g., without applying to any particular networkedenvironment or standard. In other instances, well-known structures anddevices are shown in block diagram form in order to facilitatedescribing the embodiments in additional detail.

As used in this application, the terms “component,” “module,” “system,”“interface,” “node,” “platform,” “server,” “controller,” “entity,”“element,” “gateway,” or the like are generally intended to refer to acomputer-related entity, either hardware, a combination of hardware andsoftware, software, or software in execution or an entity related to anoperational machine with one or more specific functionalities. Forexample, a component may be, but is not limited to being, a processrunning on a processor, a processor, an object, an executable, a threadof execution, computer-executable instruction(s), a program, and/or acomputer. By way of illustration, both an application running on acontroller and the controller can be a component. One or more componentsmay reside within a process and/or thread of execution and a componentmay be localized on one computer and/or distributed between two or morecomputers. As another example, an interface can comprise input/output(I/O) components as well as associated processor, application, and/orAPI components.

Further, the various embodiments can be implemented as a method,apparatus, or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement one or moreaspects of the disclosed subject matter. An article of manufacture canencompass a computer program accessible from any computer-readabledevice or computer-readable storage/communications media. For example,computer readable storage media can comprise but are not limited tomagnetic storage devices (e.g., hard disk, floppy disk, magnetic strips. . . ), optical disks (e.g., compact disk (CD), digital versatile disk(DVD) . . . ), smart cards, and flash memory devices (e.g., card, stick,key drive . . . ). Of course, those skilled in the art will recognizemany modifications can be made to this configuration without departingfrom the scope or spirit of the various embodiments.

In addition, the word “example” or “exemplary” is used herein to meanserving as an example, instance, or illustration. As used in thisapplication, the term “or” is intended to mean an inclusive “or” ratherthan an exclusive “or.” That is, unless specified otherwise, or clearfrom context, “X employs A or B” is intended to mean any of the naturalinclusive permutations. That is, if X employs A; X employs B; or Xemploys both A and B, then “X employs A or B” is satisfied under any ofthe foregoing instances. In addition, the articles “a” and “an” as usedin this application and the appended claims should generally beconstrued to mean “one or more” unless specified otherwise or clear fromcontext to be directed to a singular form.

Terms like “user equipment” or similar terminology, refer to a wired orwireless communication-capable device utilized by a subscriber or userof a wired or wireless communication service to receive or convey data,control, voice, video, sound, gaming, or substantially any data-streamor signaling-stream. Data and signaling streams can be packetized orframe-based flows. Further, the terms “user,” “subscriber,” “consumer,”“customer,” and the like are employed interchangeably throughout thesubject specification, unless context warrants particular distinction(s)among the terms. It should be noted that such terms can refer to humanentities or automated components supported through artificialintelligence (e.g., a capacity to make inference based on complexmathematical formalisms), which can provide simulated vision, soundrecognition and so forth.

Furthermore, it is noted that the term “cloud” as used herein can referto a set of servers, communicatively and/or operatively coupled to eachother, that host a set of applications utilized for servicing userrequests. In general, the cloud computing resources can communicate withuser devices via most any wired and/or wireless communication network toprovide access to services that are based in the cloud and not storedlocally (e.g., on the user device). A typical cloud computingenvironment can include multiple layers, aggregated together, thatinteract with each other to provide resources for end-users.

Aspects or features of the disclosed subject matter can be exploited insubstantially any wired or wireless communication technology; e.g.,universal mobile telecommunications system (UMTS), Wi-Fi, worldwideinteroperability for microwave access (WiMAX), general packet radioservice (GPRS), enhanced GPRS, third generation partnership project(3GPP) long term evolution (LTE), fifth generation (5G) or other nextgeneration networks, third generation partnership project 2 (3GPP2)ultra mobile broadband (UMB), high speed packet access (HSPA), Zigbee,or another IEEE 802.XX technology, low power wide area (LPWA) and/ornon-3GPP standard based solutions, such as, but not limited to, Ingenu,Sigfox, and/or LoRa, etc. Additionally, substantially all aspects of thedisclosed subject matter can be exploited in legacy (e.g., wireline)telecommunication technologies.

Internet of things (IoT), which is the future of internet connectivity,enables creation of an information rich ecosystem that can enrich modernconnected way of life and transform the way in which businesses as wellas consumers function today. Typically, IoT/machine-to-machine (M2M)devices have different characteristics than regular/commercial userequipment (UEs) (e.g., non-IoT devices, such as, but not limited to,smart phones, tablet computers, personal computers, etc.). For example,the IoT/M2M devices collectively generate a much greater number ofsignaling connections in the mobile core network as compared to regularUEs. Further, in another example, the service/application provider oftenperforms simultaneous device triggering and monitoring for targeted IoTapplications and services. In addition, the IoT/M2M devices operate in alow-power/sleep mode for longer durations (e.g., 99% of the time) ascompared to conventional non-IoT devices.

As a variety of IoT device categories emerge based on 3GPP standardsevolution supporting a multitude of services, there is an increasingdemand on the various network functions within the mobilityinfrastructure to be more intelligent, dynamic, adaptive, and flexiblewith their interworking to provide the best possible node levelfunctions and end-to-end service behaviors. The systems and methodsdisclosed herein can provide various embodiments that provide low-costdelivery of IoT services, for example, in areas that do not have networkcoverage (e.g., cellular coverage, Wi-Fi coverage, etc.), via massivelydistributed IoT gateway devices and fly-by drones. For example, multipleIoT gateway devices (e.g., also referred to as IoT agents and/or IoTgateways) can be operated under the control of fly-by drones (e.g.,unmanned aerial vehicle). In one aspect, the drones can wake up one ormore IoT gateway devices, receive data (e.g., environmental data)collected by the one or more IoT gateway devices, and fly to the nearestconnected mobility cloud network (e.g., 3G, 4G, 5G network, etc.) totransfer the collected data to a software-defined networking (SDN)network for further processing. Further, the embodiments disclosedherein describe a low-power protocol that can be utilized to communicatebetween the drones and IoT gateway devices.

Referring initially to FIG. 1, there illustrated is an example system100 that depicts a high-level network architecture that facilitates dataanalytics for IoT fields, according to one or more aspects of thedisclosed subject matter. Typically, system 100 can provide acost-efficient approach to deliver network connectivity to enable IoTservices, for example, within remote areas that do not have (or havevery limited) network coverage. As an example, infrastructure resources102 can comprise low-cost IoT gateways that are distributed across alarge area (e.g., farm) and one or more autonomous and/or automatedvehicles (e.g., drone, self driving car, etc.) that can be utilized totransfer data between the IoT gateways and a SDN cloud 104. As anexample, system 100 can be employed for various IoT applications, suchas, but not limited to, agriculture, smart cities, wildlife and/orenvironmental research, smart manufacturing and/or industrialautomation, energy, security, FirstNet, healthcare, etc.

In an aspect, a master IoT data store 106 can receive and store datacollected from the IoT gateways via the autonomous and/or automatedvehicles. An IoT pipeline control component 108 can analyze the storeddata (e.g., using Big data analysis) to manage execution of variouspipelines related to IoT services. In one example, the IoT services canenable operations, such as, but not limited to, monitoring sensor data,creating alerts and/or notifying appropriate personnel (e.g., viadashboard(s) 110), controlling and/or managing tasks (e.g., that can beperformed by the drone, the IoT gateway, and/or other connectedcontroller devices), etc. As an example, an SDN-ized IoT gatewaymanagement component 112 can comprise vehicle management components(e.g., drone controller) that can utilize defined drone behavior andpolicy data (e.g., user defined policy and/or operator-defined policy)specified by the IoT delivery diversification component 114 to enablethe IoT services.

In one example embodiment, system 100 can be utilized in theagricultural sector, where farms/fields span large areas (e.g., hundredto thousands of acres) that typically do not have network connectivity.Moreover, conventional agriculture fields lack low-cost automation andoptimization. Given the large areas that are sparsely populated and/orremote, they typically lack network connectivity and power. Manuallyoperating sensors distributed across just fields can be extremelytedious and time consuming. In contrast, system 100 can provide IoTtechnologies that are programmable and under control of a SDN to enableeconomy of scale. In this example embodiment, massively distributed IoTgateways comprising and/or coupled to one or more sensors (e.g.,environmental sensor) can be deployed across the field/farm. Moreover,the IoT gateways can comprise mobile network operator (MNO)-certifiedgateways that can be self-installed, powered by solar energy, andoperate under control of a IoT SDN cloud on boarded by one or morefly-by drones. For example, the drone(s) empowered by SDN protocols(e.g., broadcast, multicast, unicast, etc.) can wake/trigger the IoTgateways adaptively and can perform data collection and/or configurationtasks (e.g., defined by the SDN cloud 104) while flying in closeproximity to the IoT gateways (e.g., approximately less the 300-400meters above the IoT gateways). The drone(s) can then deliver thecollected data to a nearby communication network (e.g., mobilitynetwork) and return for the next batch of IoT gateway data collections(e.g., as requested by the SDN cloud 104).

Referring now to FIGS. 2A-2B, there illustrated are example systems(200, 250) that facilitate management of IoT gateways via fly-by drones,in accordance with an aspect of the subject disclosure. In one example,the systems (200, 250) can comprise massively distributed IoT gateways202 that can be deployed in remote areas that do not have networkcoverage (and/or have limited network coverage). The IoT gateways 202can be embedded with and/or coupled to one or more sensors, for example,that measure environmental data. Moreover, network connectivity, andthus IoT services, can be provided to the IoT gateways 202 by utilizingone or more drones 204 that facilitate a transfer of data between theIoT gateways 202 and the SDN cloud 104. It is noted that the SDN cloud104 can comprise functionality as more fully described herein, forexample, as described above with regard to system 100. Although, thesystems and methods disclosed herein are described with respect tofly-by drones, it is noted that the subject disclosure is not limited todrones and that most any partially and/or fully autonomous mobilevehicle and/or device can be utilized.

According to an aspect, mobile network operators (MNOs) can employsystem 200 to provide IoT services by utilizing low-cost IoT gateways202 (e.g., each costing less than $10), wherein their mobile networks(e.g., LTE, 5G, etc.) can be extended with network-operated drone(s) 204to communicate with and manage the IoT gateways 202. The IoT gateways202 can be distributed across large areas (e.g., fields, farms, forests,etc.) and can employ most any sensor (e.g., temperature, humidity,moisture, light, camera, etc.) associated with an IoT service related tothe MNO's customers. Power conservation of the IoT gateways 202 iscritical to maximize longevity in the field and accordingly, the IoTgateways 202 can operate utilizing low-power communication protocols.Ideally, the IoT gateways 202 can operate in a low-power/sleep mode andcan be woken up, for example, only to perform measurements and/or datacollection tasks and/or to communicate with the drone 204. Further,since the drone 204 flies in close proximity (e.g., less than 400 metersaway) to the IoT gateways 202, the transmission power utilized forcommunication can also be reduced. As an example, IoT gateways 202and/or drone 204 can be owned, leased, and/or managed by the MNO.

According to an embodiment, drone 204 can be configured by the SDN cloud104. For example, as shown in FIG. 2A, the drone 204 can enter (or belocated within) a coverage area 206 of an access point 208 (e.g., macroaccess point, base station, eNodeB, HnodeB, femto access point, etc.) ofthe communication network (e.g., mobility network) to communicate withthe SDN cloud 104. The drone 204 can receive (e.g., periodically, inresponse to an event, on-demand, etc.) instruction data from the SDNcloud 104. The instruction data can comprise, but is not limited to,geographical location of one or more of the IoT gateways 202,configuration data that is to be provided to one or more of the IoTgateways 202, etc. As an example, the configuration data can comprise atask and/or workload that is to be performed by a IoT gateway (e.g.,collect specific measurements, a time and/or frequency at whichmeasurement data is to be captured, etc.).

As shown at FIG. 2B, on receiving the instruction data, drone 204 canfly, via a determined route (e.g., determined by the drone 204 and/orthe SDN cloud 104) near (e.g., 300-400 meters above) the one or more IoTgateways 202 to initiate communication with the IoT gateways 202. As anexample, the drone 204 can transmit trigger signals to wake up the oneor more IoT gateways 202 and once the one or more IoT gateways 202 havewoken up, the drone 204 can transfer the configuration data to the oneor more IoT gateways 202 and/or receive measurement data from the one ormore IoT gateways 202. According to an aspect, low-power transmissionscan be utilized to facilitate the communications between the drone 204and the one or more IoT gateways 202. As an example, most any wirelesscommunication technologies (e.g., licensed and/or unlicensedtechnologies) can be utilized for the communication. In another example,the drone 204 can communicate via broadcast, multicast, and/or unicastcommunication protocols.

According to an embodiment, after data acquisition from the one or moreIoT gateways 202, the drone 204 can return within the coverage area ofthe nearest access point (e.g., access point 208 or a different accesspoint (not shown) coupled to the SDN cloud 104), couple to the accesspoint, and transfer the measurement data collected from the one or moreIoT gateways 202 to the SDN cloud 104 for further processing. As anexample, the SDN cloud 104 can analyze the measurement data and presentthe results to a subscriber via a dashboard portal, generate reports,notifications, and/or alerts, control operations (e.g., turn onsprinklers, reduce water supply, control fertilizer spray, etc.), and/ordetermine new instruction data for the drone 204 (or a disparate drone).In an aspect, after the transfer of data (and/or at most any othertime), the drone 204 can dock at a recharging station to charge itsbattery and/or refuel.

In some embodiments, drone 204 can be utilized to place an IoT gatewayat a specified location and/or pick up an IoT gateway (e.g., a faultyIoT gateway) from a specified location. Additionally, or optionally,drone 204 can act like a watchdog, wherein it can sense data (e.g.,motion, heat, sound, temperature, etc.) that can trigger actions (e.g.,data collection from IoT gateways 202 and/or ping for new instructionsfrom SDN cloud 104, etc.). In another embodiment, drone 204 cancommunicate with other drones in the area, for example, for loadbalancing and/or coordination of tasks.

Referring now to FIG. 3, there illustrated is an example system 300 thatcomprises an IoT gateway that is managed by a SDN cloud by utilizingfly-by drone(s), in accordance with an aspect of the subject disclosure.As an example, the IoT gateway 202 can comprise a low-cost, low-power,MNO-managed gateway that can be deployed in remote and/or inaccessibleareas that typically do not have network coverage (or have very limitednetwork coverage). Generally, the cost of the IoT gateway 202 can bevery low (e.g., less than 10 USD) and it can be positioned manually orby the drone 204 at defined locations or within defined areas. In oneaspect, the size of the IoT gateway 202 can be fairly small (e.g., 4×4×4cubes) and it can be environmentally packaged for withstanding high heatand/or low temperatures. As an example, the IoT gateway 202 can utilizeembedded solar panels and/or high-efficiency batteries (e.g., batteryback-up) as a power source. It is noted that the IoT gateway 202 anddrone 204 can comprise functionality as more fully described herein, forexample, as described above with regard to system 200.

In one aspect, the IoT gateway 202 can comprise (and/or be coupled to)one or more sensors 302, such as but not limited to, a camera, atemperature sensor, a humidity sensor, a light sensor, an air qualitysensor, a gas levels measurement sensor, etc. In the example ofagricultural applications, wherein the IoT gateway 202 is deployedwithin a field, most any sensors that measure parameters, such as, butnot limited to, soil temperature, pH levels, chemical compositions,moisture, and/or humidity, light density, electromagnetic spectrum toultraviolet and/or infrared rays, etc. can be utilized. The measurementscan be performed during time periods specified within configuration data304 defined by the SDN cloud (e.g., based on user preferences, operatorpreferences, power optimization policies, on-demand when triggered bythe drone 204, etc.). In one aspect, the configuration data 304 canspecify what data is to be captured and a frequency of the data capture.For example, during a seeding or germination phase associated with acrop cycle, the configuration data 304 can indicate that soil parametersbe measured more frequently and/or during a harvest phase of the cropcycle, the configuration data 304 can indicate that photos be capturedmore frequently to enable accurate prediction of ripeness. In anotherexample, during a drought, water levels and/or moisture levels can bemonitored more closely. Further, measurement data 306 captured by thesensors 302 can be stored within data store 308. As an example, themeasurement data 306 can be compressed, encrypted, time stamped, and/orlinked with an identifier of the IoT gateway 202.

To conserve power and extend battery life, the IoT gateway 202 remainsin a sleep or low-power mode unless woken-up to collect measurement data306 and/or communicate with the drone 204. In one aspect, acommunication component 310 can comprise a wireless electrical switchthat controls an operation mode of the IoT gateway 202 and that can beturned on based on a trigger signals received from drone 204. Forexample, the IoT gateway 202 can comprise a low-power receiver thatlistens for a signal, for example, a presence of energy on a radiofrequency (RF) band and/or other technology (e.g., Bluetooth, Wi-Fi,GWave, etc.). Additionally, or alternatively, the IoT gateway 202 cancomprise an acoustic sensor that can trigger the electronic switch inresponse to detecting a sound of the drone 204 as it flies close to theIoT gateway 202. When the electrical switch is turned on, the IoTgateway 202 can be woken up from the sleep/low-power mode and thecommunication component 310 can facilitate a communication with thedrone 204. In one aspect, security component 312 can be utilized toverify authorization of the drone 204 to communicate with the IoTgateway 202 (e.g., based on drone identifier, drone type, and/or mostany credential data, etc). If verified that the drone 204 is authorizedto communicate with the IoT gateway 202, the communication component 310can transfer the measurement data 306 (e.g., linked with a deviceidentifier associated with the IoT gateway 202) to the drone 204 and/orcan receive, from the drone 204, configuration data 304 (and/or updatesto the configuration data 304) that can be stored within data store 308.In some embodiments, the IoT gateway 202 can also comprise (or becoupled to) one or more controller elements (not shown), wherein theconfiguration data 304 can specify tasks to be performed by thecontroller elements, for example, turning on sprinklers, spraying morepesticides, etc. As an example, the measurement data 306 can becompressed for reduced impact on power level needed for communicationwith the drone 204. Alternatively, if determined that the drone 204 isnot authorized to communicate with the IoT gateway 202, thecommunication component 310 can prohibit communication with the drone204 and trigger the IoT gateway 202 to reenter the sleep/low-power mode.

According to an embodiment, the communication component 310 can employmost any low-cost and/or low-power communication technology and/orprotocol for communication with the drone 204, such as, but not limitedto Wi-Fi, LTE, citizens broadband radio service (CBRS), Bluetooth, etc.In one aspect, the IoT gateway 202 can comprise multiple communicationmodules that utilize different communication technologies and/orprotocols and the communication component 310 can select and utilize themost efficient interface for the communication. Once the data transferbetween the IoT gateway 202 and the drone 204 is completed, thecommunication component 310 can trigger the IoT gateway 202 to reenterthe sleep/low-power mode.

Referring now to FIG. 4, there illustrated is an example system 400comprising a fly-by drone that can be utilized to facilitatecommunication between distributed IoT gateways and a SDN cloud of amobility network, according to an aspect of the subject disclosure. Thedrone 204, empowered by SDN communication protocols, can wake/triggerthe IoT gateways adaptively and perform data collection and/orconfiguration tasks while flying close to the IoT gateways. Accordingly,the IoT gateways can conserve power by utilizing low-power transmissionsto communicate with drone 204. Further, the drone 204 can deliver thecollected data (e.g., measurement data 306) to nearby mobility networkand return for the next batch of IoT gateway data collections and/orconfigurations. It is noted that the drone 204 can comprisefunctionality as more fully described herein, for example, as describedabove with regard to system 200, 250, and 300.

In one embodiment, the drone 204 can be activated at most any time, forexample, periodically, in response to receiving instructions from theSDN cloud, in response to receiving triggers from external sensors(e.g., acoustic sensor, temperature sensor, air quality sensor, lightsensor, etc.). Typically, the drone 204 can couple to the SDN cloud, viamost any radio access network (e.g., LTE, 5G, 3G, etc.). In one aspect,the drone can comprise a subscriber identity module (SIM) and facilitateSIM-based authentication to connect to the radio access network.According to an aspect, an instruction reception component 402 canreceive instruction data from the SDN cloud (e.g., periodically, inresponse to an event, on-demand, etc.) and store the receivedinstruction data in data store 414. For example, the instruction datacan specify when to fly, a set of IoT gateways from which data is to becollected, a set of IoT gateways that are to be reconfigured,configuration data, etc.

Based on the received instruction data, a route determination component404 can be utilized to determine an optimal flying path for the drone204, for example, based on a location of the IoT gateways (e.g.,determined via global position system (GPS) information), and determinean optimal location and/or time for which the drone 204 is to stop (e.g.hover) while communicating with the IoT gateways. In one embodiment, thedrone 204 can slowly move near/above each IoT gateway, wake up thecommunication channels on the IoT gateway (e.g., by employing triggeringcomponent 406), perform a handshake, and perform the instructed dataacquisition and/or data configuration tasks (e.g., by employing datacollection component 408 and configuration component 410 respectively).In another embodiment, the drone 204 can simultaneously (orsubstantially simultaneously) wake up the communication channels on agroup of IoT gateways (e.g., by employing triggering component 406)based on utilizing broadcast and/or multicast communications. In yetanother embodiment, the drone 204 can dynamically wake up (e.g., byemploying triggering component 406) the communication channels on selectIoT gateways that determined to operate on demand. As an example, thetriggering component 406 can transmit a signal via most any wirelesstechnology (e.g., cellular, Bluetooth, Wi-Fi, GWave, etc.) that can bedetected by a receiver of the IoT gateway, which in turn can turn on theIoT gateway (e.g., exit the low-power/sleep mode). Once the dataacquisition and/or data configuration tasks are completed, the IoTgateways can be returned to a low-power/sleep mode.

The communication between the drone 204 and the IoT gateway can befacilitated via low-cost and/or low-power signaling. As an example, theIoT gateways can communicate via different protocols. In one aspect, thedata collection component 408 can receive measurement data (e.g., sensorrecords and/or logs with corresponding timestamps) that has been linkedto the respective IoT gateways (e.g., based on a gateway ID). As anexample, the measurement data can be stored within data store 414.Further, the configuration component 410 can transfer, to one or moreIoT gateways, configuration data (e.g., determined and provided by theSDN cloud) that can be utilized to program the one or more IoT gateways.For example, the configuration data can comprise, but is not limited to,software upgrades, sensor settings, data collection policies and/orpreferences, etc.

Once the data collection and/or configuration tasks have been completed,the drone 204 can fly towards and enter an area having network coverage,connect to a radio access network, and provide the measurement data tothe SDN cloud (e.g., by employing a data forwarding component 416) insecure manner. Further, the drone 204 can refuel and/or recharge andstandby until new instructions (e.g., for data acquisition and/orgateway configuration) are received from the SDN cloud. In some example,embodiments, the drone 204 can perform the data acquisition from the IoTgateways and the transfer of acquired data to the SDN cloudperiodically, for example, based on operator and/or user definedpolicies.

Additionally, or optionally, the drone 204 can comprise a gatewayrelocation component 412 that can be utilized to physically changelocations of the IoT gateways, place additional IoT gateways atdetermined/defined locations (e.g., where more detailed and/or localizedmeasurements are needed), remove existing IoT gateways from definedareas (e.g., in response to determining that the IoT gateway is notfunctioning properly and/or is non responsive). As an example, the SDNcloud can instruct the gateway relocation component 412 to move, remove,and/or redistribute the IoT gateways within a defined area (e.g., afield/farm). In these example scenarios, the drone 204 can compriseretractable arms (and/or other mechanisms) that can be utilized to pickup and/or drop off the IoT gateway. According to an embodiment, acollection of drones can be operated in coordinated mode, with clearflying paths, to capture the IoT gateways.

It is noted that the data stores described herein (e.g., data store 308and data store 414) can comprise volatile memory(s) or nonvolatilememory(s) or can comprise both volatile and nonvolatile memory(s).Examples of suitable types of volatile and non-volatile memory aredescribed below with reference to FIG. 12. The memory (e.g., datastores, databases) of the subject systems and methods is intended tocomprise, without being limited to, these and any other suitable typesof memory.

FIG. 5 illustrates an example system 500 that provides IoT services todistributed IoT gateways via one or more fly-by drones, according to anaspect of the subject disclosure. As an example, MNOs can introduce IoTservices in remote regions that do not have network coverage, byutilizing fly-by drone(s) that link IoT gateways deployed within theremote regions to the SDN cloud. It is noted that the SDN cloud 104 cancomprise functionality as more fully described herein, for example, asdescribed above with regard to systems 100-400.

According to an aspect, the fly-by drone(s) can collect data from theIoT gateways (e.g., periodically and/or on-demand) and couple to a RANto forward the data to a data reception component 502. In one example,in addition to the collected data, the data reception component 502 canreceive data from one or more other data sources, such as, but notlimited to a local data store (not shown) that stores informationregarding the IoT gateways (e.g., current configurations, capabilities,features, location, etc.), operator preferences, user preferences,service provider preferences, etc., and/or an external data store(s)(not shown), for example, web servers, content servers, etc. thatprovide additional information (e.g., weather information, news and/ortraffic reports, event data, meteorological data, etc.) that can beutilized to enable the IoT service and/or to reconfigure the IoTgateways.

Further, an analysis component 504 can evaluate the received data (e.g.,using Big data analysis, machine learning, etc.) to determine one ormore actions. As an example, based on the analysis, a feedback and alertreporting component 506 can determine display data that can bepresented, via dashboards accessible to a subscriber (e.g., via thesubscriber's user equipment), network operator, and/or service provider.In another example, in response to determining that defined alertcriteria are met (e.g., measured values exceed defined thresholds),appropriate devices and/or personnel can be notified, for example, totake actions, such as, but not limited to, adjust IoT gateway and/ordrone settings, instruct control systems (e.g., increase/decrease watersupply, add fertilizer, add pesticides, start harvesting crops, etc.),and the like. Further, an instruction determination component 508, canbe utilized to generate new instructions and/or configurations for thedrone and/or IoT gateways (e.g., frequency of data collection, whichsensors are to be activated, which sensors are to be deactivated, etc.).The instructions and/or configurations can be transferred to the droneat most any time, for example, periodically, in response to determiningthat the drone has coupled to the network, in response to determiningthat the drone has completed a transferred data acquired from the IoTgateways, etc.

As an example, in agricultural applications, the analysis component 504can determine disease and/or diagnosis based on photos of plants, whichcan be forwarded to experts via the feedback and alert reportingcomponent 506. In another example, the analysis component 504 candetermine an optimal level of nutrients that are to be added to afertilizer mix at different locations in a field, for example, based onsoil composition data sensed by the distributed IoT gateways. In yetanother example, the analysis component 504 can determine an optimalwater level that is to be provided to the crops in the field based onmoisture, temperature, and/or humidity levels sensed by the distributedIoT gateways. In yet another example, the analysis component 504 candetermine if the crops are ready for harvest for example, based on ananalysis of photos of fruits and/or vegetables, captured by thedistributed IoT gateways. Moreover, the data determined by the analysiscomponent 504 can be presented to a subscriber and/or provided to acontrol system that can automatically perform the desired actions (e.g.,open a valve, reduce water supply, create a fertilizer mixture, etc.).

Further, the analysis component 504 can determine, based on the analysisof the received data, configuration data that can configure orreconfigure one or more IoT gateways. For example, different informationcan be required for analysis at different times and accordingly, theanalysis component 504 can configure the one or more IoT gateways tocapture the required data at a particular time, for example, based ondefined policies and/or if more details are required at specificlocations and/or times. The instruction determination component 508 canforward the configuration data to one or more drones that can fly nearthe one or more IoT gateways to transfer the configuration data to theone or more IoT gateways.

Additionally, or optionally, the analysis component 504 can alsodetermine, based on the analysis of the received data, a distribution ofthe IoT gateways within a field (or other region) and can instruct oneor more drones to relocate the IoT gateways to specific locations. Inanother example, the analysis component 504 can determine faulty IoTgateways that are not operating properly and can instruct a drone tomove them to a repair facility. In yet another example, the analysiscomponent 504 can determine areas where additional information isrequired and can instruct the drone to pick up additional IoT gatewaydevice(s), from a network operator facility, and place them at definedlocations within the areas.

Referring now to FIG. 6, there illustrated is an example system 600 thatemploys an artificial intelligence (AI) component (602) to facilitateautomating one or more features in accordance with the subjectembodiments. It can be noted that the SDN cloud 104, data receptioncomponent 502, analysis component 504, feedback and alert reportingcomponent 506, and instruction determination component 508 can comprisefunctionality as more fully described herein, for example, as describedabove with regard to systems 100-500.

In an example embodiment, system 600 (e.g., in connection with providingIoT services.) can employ various AI-based schemes (e.g., intelligentprocessing/analysis, machine learning, etc.) for carrying out variousaspects thereof. For example, a process for analyzing data measured byIoT gateways, determining tasks to be performed, determiningconfiguration of the IoT gateways, etc. can be facilitated via anautomatic classifier system implemented by AI component 602. Moreover,the AI component 602 can exploit various artificial intelligence (AI)methods or machine learning methods. Artificial intelligence techniquescan typically apply advanced mathematical analysis—e.g., decision trees,neural networks, regression analysis, principal component analysis (PCA)for feature and pattern extraction, cluster analysis, genetic algorithm,or reinforced learning—to a data set. In particular, AI component 602can employ one of numerous methodologies for learning from data and thendrawing inferences from the models so constructed. For example, hiddenmarkov models (HMMs) and related prototypical dependency models can beemployed. General probabilistic graphical models, such asDempster-Shafer networks and Bayesian networks like those created bystructure search using a Bayesian model score or approximation can alsobe utilized. In addition, linear classifiers, such as support vectormachines (SVMs), non-linear classifiers like methods referred to as“neural network” methodologies, fuzzy logic methodologies can also beemployed.

As will be readily appreciated from the subject specification, anexample embodiment can employ classifiers that are explicitly trained(e.g., via a generic training data) as well as implicitly trained (e.g.,via observing device/operator preferences, historical information,receiving extrinsic information, type of service, type of device, etc.).For example, SVMs can be configured via a learning or training phasewithin a classifier constructor and feature selection module. Thus, theclassifier(s) of AI component 602 can be used to automatically learn andperform a number of functions, comprising but not limited to determiningaccording to a predetermined criteria, when and which actions are to beperformed (e.g., opening/closing a valve, adding fertilizer, initiateharvesting of crops, changing irrigation controls, etc.), notificationsprovided to a subscriber, configuration of IoT gateways and/or drones,load balancing between drones, etc. The criteria can comprise, but isnot limited to, historical patterns and/or trends, network operatorpreferences and/or policies, customer preferences, predicted trafficflows, event data, latency data, reliability/availability data, currenttime/date, sensor data, weather data, type of IoT device, news, and thelike.

FIGS. 7-11 illustrate flow diagrams and/or methods in accordance withthe disclosed subject matter. For simplicity of explanation, the flowdiagrams and/or methods are depicted and described as a series of acts.It is to be understood and noted that the various embodiments are notlimited by the acts illustrated and/or by the order of acts, for exampleacts can occur in various orders and/or concurrently, and with otheracts not presented and described herein. Furthermore, not allillustrated acts may be required to implement the flow diagrams and/ormethods in accordance with the disclosed subject matter. In addition,those skilled in the art will understand and note that the methods couldalternatively be represented as a series of interrelated states via astate diagram or events. Additionally, it should be further noted thatthe methods disclosed hereinafter and throughout this specification arecapable of being stored on an article of manufacture to facilitatetransporting and transferring such methods to computers. The termarticle of manufacture, as used herein, is intended to encompass acomputer program accessible from any computer-readable device orcomputer-readable storage/communications media.

Referring now to FIG. 7 there illustrated is an example method 700 thatfacilitates utilization of SDN-controlled massively distributed IoTgateways to enable IoT services, according to an aspect of the subjectdisclosure. In an aspect, method 700 can be implemented by one or moreIoT gateways (e.g., IoT gateways 202) of a communication network (e.g.,cellular network). The IoT gateways can be deployed in remote locationsthat typically do not have network coverage via traditional accesspoints (e.g., macro access points, Wi-Fi access points, femto accesspoints, etc.). In one aspect, the IoT gateways can be embedded with(and/or coupled to) one or more sensors, for example, that captureenvironmental data. At 702, sensor data can be captured by and storedwithin the IoT gateway. As an example, the sensor data can be capturedperiodically, based on instructions provided by an SDN, and/or on-demand(e.g., when woken-up/requested by a drone). In one aspect, the sensordata can be encrypted and/or compressed and stored within a data storeof the IoT gateway. In another aspect, the sensor data can be linkedwith timestamps (e.g., indicative of a time that the data was captured)and/or an identifier associated with the IoT gateway.

Typically, to minimize power consumption and extend battery life, theIoT gateway can remain in a sleep and/or low-power mode (e.g., whereincommunication radios are switched off) unless woken-up based on varioustriggers. At 704, trigger data can be received. For example, the triggerdata can comprise a signal transmitted by a fly-by drone that wants toinitiate communication with the IoT gateway. In one aspect, the signalcan be transmitted via most any low-power radio technology. On receivingthe trigger data, at 706, the communication radio of the IoT gateway canbe switched on. At 708, communication can be initiated with anauthorized drone. As an example, the communication can be facilitatedvia most any communication technology/protocol. Moreover, at 710, thesensor data can be transferred to the drone (e.g., which can thenforward the sensor data to the SDN). Further at 712, configuration data,that has been determined by the SDN, can be received from the drone andat 714, the IoT gateway can be configured based on the configurationdata. For example, the configuration data can comprise, but is notlimited to, software updates, instructions on activating/deactivatingspecific sensors, data collection parameters and/or frequency, etc.

FIG. 8 illustrates an example method 800 for utilizing a fly-by drone tofacilitate communication between a SDN cloud and distributed IoTgateways, according to an aspect of the subject disclosure. As anexample, method 800 is not limited to being implemented by a drone butcan be implemented by most any autonomous mobile device (e.g., a selfdriving connected car) of a communication network (e.g., cellularnetwork). In an aspect, the drone can comprise a cellular radio that cancommunicate with the SDN, for example, via a wireless access point. At802, instruction data can be received from the SDN. As an example, theinstruction data can indicate a set of IoT gateways, from which data isto be acquired and/or a set of IoT gateways, to which data (e.g.,configuration data) is to be transferred.

At 804, based on the instruction data an optimal route for the drone(e.g., that enables the drone to fly near the IoT gateways) can bedetermined. At 806, the IoT gateways can be adaptively triggered as thedrone moves along the route. Typically, the IoT gateways are in alow-power, standby, and/or sleep mode and can be woken up bytransmitting a trigger signal on a specified communication band. At 808,secure communication between the drone and one or more of the IoTgateways can be initiated to transfer configuration data received fromthe SDN cloud to the IoT gateways and/or receive sensor data collectedby the IoT gateways. As an example, the communication can comprise mostany broadcast, multicast, and/or unicast communication protocols.

Further, at 810, the drone can be routed back within an area withnetwork connectivity (e.g., within a coverage area of an access point ofthe network) and can be coupled to the network. Furthermore, at 812, thesensor data collected by the drone can be transferred, via the network,to the SDN for further processing.

FIG. 9 illustrates an example method 900 for managing distributed IoTgateways based on instructions received from a SDN cloud that aredelivered via an autonomous mobile device, according to an aspect of thesubject disclosure. As an example, method 900 can be implemented by oneor more network devices of a communication network (e.g., cellularnetwork). In an aspect, at 902, sensor data, collected by massivelydistributed IoT gateways, can be received via the autonomous mobiledevice, such as, but not limited to a drone. At 904, the sensor data canbe analyzed (e.g., by employing big data analytics, machine learningtechniques, etc.). As an example, additional data received from one ormore network servers and/or third-party servers can also be utilized forthe analysis.

At 906, based on a result of the analysis, configuration data associatedwith a set of the IoT gateways can be determined. For example, theconfiguration data can be utilized to program the IoT gateway and/orupdate capabilities of the IoT gateway. Further, at 908, theconfiguration data can be transferred to the set of the IoT gateways viathe autonomous mobile device (e.g., a drone).

FIG. 10 illustrates an example method 1000 for managing an autonomousmobile device utilized to facilitate communications between distributedIoT gateways and a communication network, according to an aspect of thesubject disclosure. As an example, method 1000 can be implemented by oneor more network devices of the communication network (e.g., cellularnetwork). In an aspect, at 1002, sensor data, collected by massivelydistributed IoT gateways, can be received via the autonomous mobiledevice, such as, but not limited to a drone. At 1004, the sensor datacan be analyzed (e.g., by employing big data analytics, machine learningtechniques, etc.). As an example, additional data received from one ormore network servers and/or third-party servers can also be utilized forthe analysis.

At 1006, based on a result of the analysis, instructions and/or tasks tobe performed by the autonomous mobile device can be determined. Forexample, the instructions can specify when the autonomous mobile deviceis to travel towards the IoT gateways, IoT gateways with which it cancommunicate, IoT gateways to which it can transfer data, IoT gatewaysfrom which it can receive data, type of communication protocol that isto be utilized for communication with the IoT gateways, location of theIoT gateways, etc. Further, in another example, tasks can comprise,relocating a IoT gateway(s), adding a supplementary IoT gateway(s)within a defined area, removing an existing IoT gateway(s) from thedefined area, etc. At 1008, the instructions and/or tasks can betransferred to the autonomous mobile device, for example, in response todetermining that the autonomous mobile device has coupled to the network(e.g., via a RAN).

FIG. 11 illustrates an example method 1100 for monitoring informationsensed by distributed IoT gateways that communicate with a SDN cloud viaan autonomous mobile device, according to an aspect of the subjectdisclosure. As an example, method 1100 can be implemented by one or morenetwork devices of the communication network (e.g., cellular network).In an aspect, at 1102, sensor data, collected by massively distributedIoT gateways, can be received via the autonomous mobile device, such as,but not limited to a drone. At 1104, the sensor data can be analyzed(e.g., by employing big data analytics, machine learning techniques,etc.). As an example, additional data received from one or more networkservers and/or third-party servers can also be utilized for theanalysis.

At 1106, a presentation of display data, indicative of a result of theanalysis, can be facilitated via one or more dashboards accessible to anauthorized user (e.g., via a user equipment). As an example, the displaydata can comprise sensor data collected from IoT gateways, statusreports of monitored objects (e.g., status and/or overall health ofcrops), and/or recommended actions to achieve a goal (e.g., addfertilizer to improve yield), etc. Further at 1108, appropriate user(s)can be notifies regarding an alert (e.g., an unexpected state, errorcondition, etc.) that is generated based on the result of the analysis.

Referring now to FIG. 12, there is illustrated a block diagram of acomputer 1202 operable to execute the disclosed communicationarchitecture. In order to provide additional context for various aspectsof the disclosed subject matter, FIG. 12 and the following discussionare intended to provide a brief, general description of a suitablecomputing environment 1200 in which the various aspects of thespecification can be implemented. While the specification has beendescribed above in the general context of computer-executableinstructions that can run on one or more computers, those skilled in theart will recognize that the specification also can be implemented incombination with other program modules and/or as a combination ofhardware and software.

Generally, program modules comprise routines, programs, components, datastructures, etc., that perform particular tasks or implement particularabstract data types. Moreover, those skilled in the art will note thatthe inventive methods can be practiced with other computer systemconfigurations, comprising single-processor or multiprocessor computersystems, minicomputers, mainframe computers, as well as personalcomputers, hand-held computing devices, microprocessor-based orprogrammable consumer electronics, and the like, each of which can beoperatively coupled to one or more associated devices.

The illustrated aspects of the specification can also be practiced indistributed computing environments where certain tasks are performed byremote processing devices that are linked through a communicationsnetwork. In a distributed computing environment, program modules can belocated in both local and remote memory storage devices.

Computing devices typically comprise a variety of media, which cancomprise computer-readable storage media and/or communications media,which two terms are used herein differently from one another as follows.Computer-readable storage media can be any available storage media thatcan be accessed by the computer and comprises both volatile andnonvolatile media, removable and non-removable media. By way of example,and not limitation, computer-readable storage media can be implementedin connection with any method or technology for storage of informationsuch as computer-readable instructions, program modules, structureddata, or unstructured data. Computer-readable storage media cancomprise, but are not limited to, RAM, ROM, EEPROM, flash memory orother memory technology, CD-ROM, digital versatile disk (DVD) or otheroptical disk storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or other tangible and/ornon-transitory media which can be used to store desired information.Computer-readable storage media can be accessed by one or more local orremote computing devices, e.g., via access requests, queries or otherdata retrieval protocols, for a variety of operations with respect tothe information stored by the medium.

Communications media typically embody computer-readable instructions,data structures, program modules or other structured or unstructureddata in a data signal such as a modulated data signal, e.g., a carrierwave or other transport mechanism, and comprises any informationdelivery or transport media. The term “modulated data signal” or signalsrefers to a signal that has one or more of its characteristics set orchanged in such a manner as to encode information in one or moresignals. By way of example, and not limitation, communication mediacomprise wired media, such as a wired network or direct-wiredconnection, and wireless media such as acoustic, radio frequency (RF),infrared and other wireless media.

With reference again to FIG. 12, the example environment 1200 forimplementing various aspects of the specification comprises a computer1202, the computer 1202 comprising a processing unit 1204, a systemmemory 1206 and a system bus 1208. As an example, the component(s),application(s), client(s), server(s), equipment, system(s),interface(s), gateway(s), controller(s), node(s), cloud(s), entity(ies),function(s), platform(s), dashboard(s), resource(s), and/or device(s)(e.g., infrastructure resources 102, SDN cloud 104, master IoT datastore 106, IoT pipeline control component 108, IoT dashboard(s) 110,SDN-ized IoT gateway management component 112, IoT deliverydiversification component 114, IoT gateway nodes 202, drone 204, accesspoint 208, data store 308, communication component 310, securitycomponent 312, instruction reception component 402, route determinationcomponent 404, triggering component 406, data collection component 408,configuration component 410, gateway relocation component 412, datastore 414, data forwarding component 416, data reception component 502,analysis component 504, feedback and alert reporting component 506,instruction determination component 508, AI component 602, etc.)disclosed herein with respect to systems 100-600 can each comprise atleast a portion of the computer 1202. The system bus 1208 couples systemcomponents comprising, but not limited to, the system memory 1206 to theprocessing unit 1204. The processing unit 1204 can be any of variouscommercially available processors. Dual microprocessors and othermulti-processor architectures can also be employed as the processingunit 1204.

The system bus 1208 can be any of several types of bus structure thatcan further interconnect to a memory bus (with or without a memorycontroller), a peripheral bus, and a local bus using any of a variety ofcommercially available bus architectures. The system memory 1206comprises read-only memory (ROM) 1210 and random access memory (RAM)1212. A basic input/output system (BIOS) is stored in a non-volatilememory 1210 such as ROM, EPROM, EEPROM, which BIOS contains the basicroutines that help to transfer information between elements within thecomputer 1202, such as during startup. The RAM 1212 can also comprise ahigh-speed RAM such as static RAM for caching data.

The computer 1202 further comprises an internal hard disk drive (HDD)1214, which internal hard disk drive 1214 can also be configured forexternal use in a suitable chassis (not shown), a magnetic floppy diskdrive (FDD) 1216, (e.g., to read from or write to a removable diskette1218) and an optical disk drive 1220, (e.g., reading a CD-ROM disk 1222or, to read from or write to other high capacity optical media such asthe DVD). The hard disk drive 1214, magnetic disk drive 1216 and opticaldisk drive 1220 can be connected to the system bus 1208 by a hard diskdrive interface 1224, a magnetic disk drive interface 1226 and anoptical drive interface 1228, respectively. The interface 1224 forexternal drive implementations comprises at least one or both ofuniversal serial bus (USB) and IEEE 1394 interface technologies. Otherexternal drive connection technologies are within contemplation of thesubject disclosure.

The drives and their associated computer-readable storage media providenonvolatile storage of data, data structures, computer-executableinstructions, and so forth. For the computer 1202, the drives andstorage media accommodate the storage of any data in a suitable digitalformat. Although the description of computer-readable storage mediaabove refers to a HDD, a removable magnetic diskette, and a removableoptical media such as a CD or DVD, it should be noted by those skilledin the art that other types of storage media which are readable by acomputer, such as zip drives, magnetic cassettes, flash memory cards,solid-state disks (SSD), cartridges, and the like, can also be used inthe example operating environment, and further, that any such storagemedia can contain computer-executable instructions for performing themethods of the specification.

A number of program modules can be stored in the drives and RAM 1212,comprising an operating system 1230, one or more application programs1232, other program modules 1234 and program data 1236. All or portionsof the operating system, applications, modules, and/or data can also becached in the RAM 1212. It is noted that the specification can beimplemented with various commercially available operating systems orcombinations of operating systems.

A user can enter commands and information into the computer 1202 throughone or more wired/wireless input devices, e.g., a keyboard 1238 and/or apointing device, such as a mouse 1240 or a touchscreen or touchpad (notillustrated). These and other input devices are often connected to theprocessing unit 1204 through an input device interface 1242 that iscoupled to the system bus 1208, but can be connected by otherinterfaces, such as a parallel port, an IEEE 1394 serial port, a gameport, a USB port, an IR interface, etc. A monitor 1244 or other type ofdisplay device is also connected to the system bus 1208 via aninterface, such as a video adapter 1246.

The computer 1202 can operate in a networked environment using logicalconnections via wired and/or wireless communications to one or moreremote computers, such as a remote computer(s) 1248. The remotecomputer(s) 1248 can be a workstation, a server computer, a router, apersonal computer, portable computer, microprocessor-based entertainmentappliance, a peer device or other common network node, and typicallycomprises many or all of the elements described relative to the computer1202, although, for purposes of brevity, only a memory/storage device1250 is illustrated. The logical connections depicted comprisewired/wireless connectivity to a local area network (LAN) 1252 and/orlarger networks, e.g., a wide area network (WAN) 1254. Such LAN and WANnetworking environments are commonplace in offices and companies, andfacilitate enterprise-wide computer networks, such as intranets, all ofwhich can connect to a global communications network, e.g., theInternet.

When used in a LAN networking environment, the computer 1202 isconnected to the local network 1252 through a wired and/or wirelesscommunication network interface or adapter 1256. The adapter 1256 canfacilitate wired or wireless communication to the LAN 1252, which canalso comprise a wireless access point disposed thereon for communicatingwith the wireless adapter 1256.

When used in a WAN networking environment, the computer 1202 cancomprise a modem 1258, or is connected to a communications server on theWAN 1254 or has other means for establishing communications over the WAN1254, such as by way of the Internet. The modem 1258, which can beinternal or external and a wired or wireless device, is connected to thesystem bus 1208 via the serial port interface 1242. In a networkedenvironment, program modules depicted relative to the computer 1202, orportions thereof, can be stored in the remote memory/storage device1250. It will be noted that the network connections shown are exampleand other means of establishing a communications link between thecomputers can be used.

The computer 1202 is operable to communicate with any wireless devicesor entities operatively disposed in wireless communication, e.g.,desktop and/or portable computer, server, communications satellite, etc.This comprises at least Wi-Fi and Bluetooth™ wireless technologies orother communication technologies. Thus, the communication can be apredefined structure as with a conventional network or simply an ad hoccommunication between at least two devices.

Wi-Fi, or Wireless Fidelity networks use radio technologies called IEEE802.11 (a, b, g, n, etc.) to provide secure, reliable, fast wirelessconnectivity. A Wi-Fi network can be used to connect computers to eachother, to the Internet, and to wired networks (which use IEEE 802.3 orEthernet). Wi-Fi networks operate in the unlicensed 2.4 and 5 GHz radiobands, at an 11 Mbps (802.11a) or 54 Mbps (802.11b) data rate, forexample, or with products that contain both bands (dual band), so thenetworks can provide real-world performance similar to the basic 10BaseTwired Ethernet networks used in many offices.

As it employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to comprising, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory. Additionally, a processor can refer to an integratedcircuit, an application specific integrated circuit (ASIC), a digitalsignal processor (DSP), a field programmable gate array (FPGA), aprogrammable logic controller (PLC), a complex programmable logic device(CPLD), a discrete gate or transistor logic, discrete hardwarecomponents, or any combination thereof designed to perform the functionsdescribed herein. Processors can exploit nano-scale architectures suchas, but not limited to, molecular and quantum-dot based transistors,switches and gates, in order to optimize space usage or enhanceperformance of user equipment. A processor may also be implemented as acombination of computing processing units.

In the subject specification, terms such as “data store,” data storage,”“database,” “cache,” and substantially any other information storagecomponent relevant to operation and functionality of a component, referto “memory components,” or entities embodied in a “memory” or componentscomprising the memory. It will be noted that the memory components, orcomputer-readable storage media, described herein can be either volatilememory or nonvolatile memory, or can comprise both volatile andnonvolatile memory. By way of illustration, and not limitation,nonvolatile memory can comprise read only memory (ROM), programmable ROM(PROM), electrically programmable ROM (EPROM), electrically erasable ROM(EEPROM), or flash memory. Volatile memory can comprise random accessmemory (RAM), which acts as external cache memory. By way ofillustration and not limitation, RAM is available in many forms such assynchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM),double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), SynchlinkDRAM (SLDRAM), and direct Rambus RAM (DRRAM). Additionally, thedisclosed memory components of systems or methods herein are intended tocomprise, without being limited to comprising, these and any othersuitable types of memory.

Referring now to FIG. 13, there is illustrated a schematic block diagramof a computing environment 1300 in accordance with the subjectspecification. The system 1300 comprises one or more client(s) 1302. Theclient(s) 1302 can be hardware and/or software (e.g., threads,processes, computing devices).

The system 1300 also comprises one or more server(s) 1304. The server(s)1304 can also be hardware and/or software (e.g., threads, processes,computing devices). The servers 1304 can house threads to performtransformations by employing the specification, for example. Onepossible communication between a client 1302 and a server 1304 can be inthe form of a data packet adapted to be transmitted between two or morecomputer processes. The data packet may comprise a cookie and/orassociated contextual information, for example. The system 1300comprises a communication framework 1306 (e.g., a global communicationnetwork such as the Internet, cellular network, etc.) that can beemployed to facilitate communications between the client(s) 1302 and theserver(s) 1304.

Communications can be facilitated via a wired (comprising optical fiber)and/or wireless technology. The client(s) 1302 are operatively connectedto one or more client data store(s) 1308 that can be employed to storeinformation local to the client(s) 1302 (e.g., cookie(s) and/orassociated contextual information). Similarly, the server(s) 1304 areoperatively connected to one or more server data store(s) 1310 that canbe employed to store information local to the servers 1304.

What has been described above comprises examples of the presentspecification. It is, of course, not possible to describe everyconceivable combination of components or methods for purposes ofdescribing the present specification, but one of ordinary skill in theart may recognize that many further combinations and permutations of thepresent specification are possible. Accordingly, the presentspecification is intended to embrace all such alterations, modificationsand variations that fall within the spirit and scope of the appendedclaims. Furthermore, to the extent that the term “comprises” is used ineither the detailed description or the claims, such term is intended tobe inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim.

What is claimed is:
 1. An autonomous mobile device, comprising: aprocessor; and a memory that stores executable instructions that, whenexecuted by the processor, facilitate performance of operations,comprising: receiving, from a software-defined networking device of acommunication network, configuration data employable to program anInternet of things gateway device; moving within an area associated withthe Internet of things gateway device; and triggering the Internet ofthings gateway device to facilitate a transmission of the configurationdata to the Internet of things gateway device.
 2. The autonomous mobiledevice of claim 1, wherein the operations further comprise: receiving,from the Internet of things gateway device, measurement data captured bya sensor of the Internet of things gateway device; and in response todetermining that the autonomous mobile device is coupled to a radioaccess network device of the communication network, facilitating atransfer of the measurement data to the software-defined networkingdevice.
 3. The autonomous mobile device of claim 2, wherein themeasurement data is analyzed to determine an update to the configurationdata.
 4. The autonomous mobile device of claim 2, wherein themeasurement data is analyzed to determine task data indicative of a taskthat is to be performed by the autonomous mobile device.
 5. Theautonomous mobile device of claim 2, wherein the measurement data isanalyzed to determine display data that is accessible via a userequipment.
 6. The autonomous mobile device of claim 2, wherein themeasurement data is analyzed to determine alert data that is employableto notify a specified user equipment of an error condition.
 7. Theautonomous mobile device of claim 1, wherein the operations furthercomprise: based on location data indicative of a geographical locationof the Internet of things gateway device, determining route dataindicative of a route via which the autonomous mobile device is totravel.
 8. The autonomous mobile device of claim 1, wherein theoperations further comprise: receiving, from the software-definednetworking device of a communication network, instruction dataindicative of an instruction to relocate the Internet of things gatewaydevice; and based on the instruction data, facilitating a relocation ofthe Internet of things gateway device.
 9. The autonomous mobile deviceof claim 1, wherein the triggering comprises transmitting a triggersignal via a defined communication channel.
 10. The autonomous mobiledevice of claim 1, further comprising a drone equipped with wirelesscommunications functionality.
 11. A method, comprising: receiving, by asystem comprising a processor, instruction data from a software-definednetworking device of a communication network, wherein the instructiondata comprises an instruction associated with a data collection taskassociated with an Internet of things gateway device that is to beperformed via an autonomous mobile device, and wherein the instructiondata further comprises configuration data employable to configure theInternet of things gateway device; in response to the receiving,facilitating, by the system, a routing of the autonomous mobile devicealong a path that is within a defined distance from the Internet ofthings gateway device; facilitating, by the system, a first securecommunication between the autonomous mobile device and the Internet ofthings gateway device to initiate an execution of the data collectiontask, wherein the execution comprises a transfer of measurement datafrom the Internet of things gateway device to the autonomous mobiledevice, wherein the measurement data comprises information that has beenrecorded via a sensor of the Internet of things gateway device, andwherein the first secure communication comprises facilitating the firstsecure communication to transfer the configuration data from theautonomous mobile device to the Internet of things gateway device; andfacilitating, by the system, a second secure communication thattransfers the measurement data from the autonomous mobile device to thesoftware-defined networking device.
 12. The method of claim 11, whereinthe facilitating the second secure communication comprises facilitatingthe second secure communication to initiate an analysis of themeasurement data to determine updated configuration data.
 13. The methodof claim 11, wherein the facilitating the second secure communicationcomprises facilitating the second secure communication to initiate ananalysis of the measurement data to determine an error condition. 14.The method of claim 11, wherein the information comprises environmentalinformation of an environment of the sensor.
 15. A non-transitorymachine-readable storage medium, comprising executable instructionsthat, when executed by a processor of a device, facilitate performanceof operations, comprising: receiving instruction data from asoftware-defined networking device of a communication network, whereinthe instruction data comprises configuration information associated witha configuration task associated with an Internet of things gatewaydevice that is to be performed via an autonomous mobile device; inresponse to the receiving, routing the autonomous mobile device to alocation within a defined distance from the Internet of things gatewaydevice; and facilitating a secure communication between the autonomousmobile device and the Internet of things gateway device to initiate anexecution of the configuration task, wherein the execution comprises atransfer of the configuration information to the Internet of thingsgateway device from the autonomous mobile device, and wherein theconfiguration information is employable to program the Internet ofthings gateway device.
 16. The non-transitory machine-readable storagemedium of claim 15, wherein the secure communication is facilitated viaa broadcast protocol.
 17. The non-transitory machine-readable storagemedium of claim 15, wherein the secure communication is facilitated viaa multicast protocol.
 18. The non-transitory machine-readable storagemedium of claim 15, wherein the facilitating the secure communicationcomprises triggering the Internet of things gateway device to exit asleep mode of operation.
 19. The non-transitory machine-readable storagemedium of claim 15, wherein the Internet of things gateway device isdeployed in an area without network coverage.
 20. The non-transitorymachine-readable storage medium of claim 15, wherein the securecommunication is facilitated via a unicast protocol.